path: "tensorflow.feature_column"
tf_module {
  member_method {
    name: "bucketized_column"
    argspec: "args=[\'source_column\', \'boundaries\'], varargs=None, keywords=None, defaults=None"
  }
  member_method {
    name: "categorical_column_with_hash_bucket"
    argspec: "args=[\'key\', \'hash_bucket_size\', \'dtype\'], varargs=None, keywords=None, defaults=[\"<dtype: \'string\'>\"], "
  }
  member_method {
    name: "categorical_column_with_identity"
    argspec: "args=[\'key\', \'num_buckets\', \'default_value\'], varargs=None, keywords=None, defaults=[\'None\'], "
  }
  member_method {
    name: "categorical_column_with_vocabulary_file"
    argspec: "args=[\'key\', \'vocabulary_file\', \'vocabulary_size\', \'num_oov_buckets\', \'default_value\', \'dtype\'], varargs=None, keywords=None, defaults=[\'None\', \'0\', \'None\', \"<dtype: \'string\'>\"], "
  }
  member_method {
    name: "categorical_column_with_vocabulary_list"
    argspec: "args=[\'key\', \'vocabulary_list\', \'dtype\', \'default_value\', \'num_oov_buckets\'], varargs=None, keywords=None, defaults=[\'None\', \'-1\', \'0\'], "
  }
  member_method {
    name: "crossed_column"
    argspec: "args=[\'keys\', \'hash_bucket_size\', \'hash_key\'], varargs=None, keywords=None, defaults=[\'None\'], "
  }
  member_method {
    name: "embedding_column"
    argspec: "args=[\'categorical_column\', \'dimension\', \'combiner\', \'initializer\', \'ckpt_to_load_from\', \'tensor_name_in_ckpt\', \'max_norm\', \'trainable\', \'use_safe_embedding_lookup\'], varargs=None, keywords=None, defaults=[\'mean\', \'None\', \'None\', \'None\', \'None\', \'True\', \'True\'], "
  }
  member_method {
    name: "indicator_column"
    argspec: "args=[\'categorical_column\'], varargs=None, keywords=None, defaults=None"
  }
  member_method {
    name: "input_layer"
    argspec: "args=[\'features\', \'feature_columns\', \'weight_collections\', \'trainable\', \'cols_to_vars\', \'cols_to_output_tensors\'], varargs=None, keywords=None, defaults=[\'None\', \'True\', \'None\', \'None\'], "
  }
  member_method {
    name: "linear_model"
    argspec: "args=[\'features\', \'feature_columns\', \'units\', \'sparse_combiner\', \'weight_collections\', \'trainable\', \'cols_to_vars\'], varargs=None, keywords=None, defaults=[\'1\', \'sum\', \'None\', \'True\', \'None\'], "
  }
  member_method {
    name: "make_parse_example_spec"
    argspec: "args=[\'feature_columns\'], varargs=None, keywords=None, defaults=None"
  }
  member_method {
    name: "numeric_column"
    argspec: "args=[\'key\', \'shape\', \'default_value\', \'dtype\', \'normalizer_fn\'], varargs=None, keywords=None, defaults=[\'(1,)\', \'None\', \"<dtype: \'float32\'>\", \'None\'], "
  }
  member_method {
    name: "sequence_categorical_column_with_hash_bucket"
    argspec: "args=[\'key\', \'hash_bucket_size\', \'dtype\'], varargs=None, keywords=None, defaults=[\"<dtype: \'string\'>\"], "
  }
  member_method {
    name: "sequence_categorical_column_with_identity"
    argspec: "args=[\'key\', \'num_buckets\', \'default_value\'], varargs=None, keywords=None, defaults=[\'None\'], "
  }
  member_method {
    name: "sequence_categorical_column_with_vocabulary_file"
    argspec: "args=[\'key\', \'vocabulary_file\', \'vocabulary_size\', \'num_oov_buckets\', \'default_value\', \'dtype\'], varargs=None, keywords=None, defaults=[\'None\', \'0\', \'None\', \"<dtype: \'string\'>\"], "
  }
  member_method {
    name: "sequence_categorical_column_with_vocabulary_list"
    argspec: "args=[\'key\', \'vocabulary_list\', \'dtype\', \'default_value\', \'num_oov_buckets\'], varargs=None, keywords=None, defaults=[\'None\', \'-1\', \'0\'], "
  }
  member_method {
    name: "sequence_numeric_column"
    argspec: "args=[\'key\', \'shape\', \'default_value\', \'dtype\', \'normalizer_fn\'], varargs=None, keywords=None, defaults=[\'(1,)\', \'0.0\', \"<dtype: \'float32\'>\", \'None\'], "
  }
  member_method {
    name: "shared_embedding_columns"
    argspec: "args=[\'categorical_columns\', \'dimension\', \'combiner\', \'initializer\', \'shared_embedding_collection_name\', \'ckpt_to_load_from\', \'tensor_name_in_ckpt\', \'max_norm\', \'trainable\', \'use_safe_embedding_lookup\'], varargs=None, keywords=None, defaults=[\'mean\', \'None\', \'None\', \'None\', \'None\', \'None\', \'True\', \'True\'], "
  }
  member_method {
    name: "weighted_categorical_column"
    argspec: "args=[\'categorical_column\', \'weight_feature_key\', \'dtype\'], varargs=None, keywords=None, defaults=[\"<dtype: \'float32\'>\"], "
  }
}
